Real-time speed estimation of vehicles from uncalibrated view-independent traffic cameras

This paper presents a comprehensive solution for implementing a processing module on traffic cameras that is capable of tracking every vehicle in the camera frame and estimating its speed in real-time. A hybrid framework for multiple vehicle tracking is employed that utilizes Kalman filter and Hunga...

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Bibliographic Details
Main Authors: Anil Rao, Y.G., Kumar, N. Sujith, Amaresh, H.S., Chirag, H.V.
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Calibration
camera view
Cameras
Estimating
Estimation
frames per second (FPS)
homography
Hungarian algorithm
Kalman filter
Kalman filters
multiple tracking
occlusion
perspective transform
Real time
Region of Interest
Roads
top view
Tracking
Traffic engineering
Traffic flow
Transmission line matrix methods
Vehicles
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Summary:This paper presents a comprehensive solution for implementing a processing module on traffic cameras that is capable of tracking every vehicle in the camera frame and estimating its speed in real-time. A hybrid framework for multiple vehicle tracking is employed that utilizes Kalman filter and Hungarian Algorithm to resolve occlusions. A speed estimation methodology is described that is robust enough to work with camera feed from any angle without calibration and camera mounted at a minimum height of 7m. The system has been tested on computer-generated sequences as well as real-life scenarios and speed estimates have been obtained with maximum error of less than 3kmph.
ISSN:2159-3442
2159-3450
DOI:10.1109/TENCON.2015.7373162